Field of the Invention
One or more embodiments setting forth the ideas described throughout this disclosure pertain to the field of motion capture sensors that produce motion capture data, and displaying information based on motion analysis data associated with a user or piece of equipment or clothing based on previous motion analysis data from the user or other user(s) and/or piece of equipment or clothing. More particularly, but not by way of limitation, one or more aspects of the disclosure enable a wireless or closely coupled intelligent motion capture sensor in a variety of physical formats including standalone and SIM for example that obtains any combination of orientation, position, velocity, acceleration, proximity, pressure or strain and that enables use of the actual motion capture data obtained from portable wireless motion capture elements such as visual markers and sensors, radio frequency identification tags and mobile device computer systems for healthcare compliance, sporting, gaming, military, virtual reality, industrial, retail loss tracking, security, baby and elderly monitoring and other applications and in one or more embodiment includes sensor personalities that optimize the sensor for specific movements and/or pieces of equipment and/or clothing. Embodiments enable highly sophisticated calibration, power saving, dynamic sampling rates or modes, intermittent data transfer for power saving and robustness, interpolation, pairing and displays including remote displays on a mobile device or other computer, or via a local physical display.
Description of the Related Art
Known motion capture sensors are limited for a variety of reasons. One main limitation of known motion capture sensors is accuracy, another limitation is power usage. In addition, known sensors have limited functionality directed at motion and also have limited communications capabilities. Know sensors are specific to a sport or piece of equipment and are incapable of being utilized in multiple pieces of equipment by decoupling and recoupling with a second piece of equipment for example. There are no known helmet based accelerometers that are retrofittable into an existing helmet for example with or without local LED displays to indicate potential concussion level acceleration. Existing systems are known that utilize motion capture sensors to perform remote vital sign monitoring for example, but not based on motion and not based on previously stored motion data from the user or other users or piece of equipment. For example, baby monitoring would be improved significantly if the pattern of the previous motion for chest movement or breathing of the baby were compared to current motion. This allows for display of warnings that a baby's breathing is slower on a particular night than usual, which may indicate that the baby is becoming ill. This would also enable remote sleep apnea monitoring as well. For children that play video games, there are no known systems that compare motion of the game controller to previous motion of the child to determine if the child has been playing video games too much, or in comparison to other children that the child is playing an above average amount. There are no known systems that enable a display to be sent to a monitoring parent or physician based on anything other than current vital signs. The physician could also receive a display of any type of message that indicates if a child or adult is moving a certain amount or not at all or a certain amount in comparison to their usual motion during exercise. This would facilitate diabetes compliance monitoring to ensure the patient is moving enough per day and compared to their previous patterns or other patient patterns with similar demographics for example, and may save the doctor from paying higher insurance premiums if the doctor were able to remotely ensure that each patient is complying with orders. In addition, other types of motion capture includes a technique to teach effective body mechanics utilizes video recording of an athlete and analysis of the recorded video of an athlete. This technique has various limitations including inaccurate and inconsistent subjective analysis based on video for example. Another technique includes motion analysis, for example using at least two cameras to capture three-dimensional points of movement associated with an athlete. Known implementations utilize a stationary multi-camera system that is not portable and thus cannot be utilized outside of the environment where the system is installed, for example during an athletic event such as a golf tournament. These fixed installations are extremely expensive as well. Such prior techniques are summarized in U.S. Pat. No. 7,264,554, filed 26 Jan. 2006, which claims the benefit of U.S. Provisional Patent Application Ser. No. 60/647,751 filed 26 Jan. 2005, the specifications of which are both hereby incorporated herein by reference. Both disclosures are to the same inventor of the subject matter of the instant application. Regardless of the motion capture data obtained, the data is generally analyzed on a per user or per swing basis that does not contemplate processing on a mobile phone, so that a user would only buy a motion capture sensor and an “app” for a pre-existing mobile phone. In addition, existing solutions do not contemplate mobile use, analysis and messaging and/or comparison to or use of previously stored motion capture data from the user or other users or data mining of large data sets of motion capture data. To summarize, motion capture data is generally used for immediate monitoring or sports performance feedback and generally has had limited and/or primitive use in other fields.
Known systems generally utilize several passive or active markers or several sensors. There are no known systems that utilize as little as one visual marker or sensor and an app that for example executes on a mobile device that a user already owns, to analyze and display motion capture data associated with a user and/or piece of equipment. The data is generally analyzed in a laboratory on a per user or per swing basis and is not used for any other purpose besides motion analysis or representation of motion of that particular user and is generally not subjected to data mining.
There are no known systems that allow for a group of mobile devices to share data to form three-dimensional motion capture data by triangulation of visual markers. There are no known systems that allow for a mobile device without a camera to obtain images from cameras or other mobile devices with cameras to display motion capture data. In addition, known systems do not save images of users along with motion capture data for later use, including gaming, morphological comparing, compliance, tracking calories burned, work performed, monitoring of children or elderly based on motion or previous motion patterns that vary during the day and night, safety monitoring for troops when G-forces exceed a threshold or motion stops, local use of running, jumping throwing motion capture data for example on a cell phone including virtual reality applications that make use of the user's current and/or previous data or data from other users, or play music or select a play list based on the type of motion a user is performing or data mining.
There are no known mobile motion captures systems that allow for a user to align a camera correctly along the horizontal before capture of motion data having horizontally aligned images.
There are no known systems that allow for motion capture elements such as wireless sensors to seamlessly integrate or otherwise couple with a user or shoes, gloves, shirts, pants, belts, or other equipment, such as a baseball bat, tennis racquet or golf club for local analysis or later analysis in such a small format that the user is not aware that the sensors are located in or on these items. There are no known systems that provide seamless mounts, for example in the weight port of a golf club or at the end shaft near the handle so as to provide a wireless golf club, configured to capture motion data. Data derived from existing sensors is not saved in a database for a large number of events and is not used relative to anything but the performance at which the motion capture data was acquired.
In addition, for sports that utilize a piece of equipment and a ball, there are no known portable systems that allow the user to obtain immediate visual feedback regarding ball flight distance, swing speed, swing efficiency of the piece of equipment or how centered an impact of the ball is, i.e., where on piece of equipment the collision of the ball has taken place. These systems do not allow for user's to play games with the motion capture data acquired from other users, or historical players, or from their own previous performances. Known systems do not allow for data mining motion capture data from a large number of swings to suggest or allow the searching for better or optimal equipment to match a user's motion capture data and do not enable original equipment manufacturers (OEMs) to make business decisions, e.g., improve their products, compare their products to other manufacturers, up-sell products or contact users that may purchase different or more profitable products.
In addition, there are no known systems that utilize motion capture data mining for equipment fitting and subsequent point-of-sale decision making for instantaneous purchasing of equipment that fits an athlete. Furthermore, no known systems allow for custom order fulfillment such as assemble-to-order (ATO) for custom order fulfillment of sporting equipment, for example equipment that is built to customer specifications based on motion capture data mining, and shipped to the customer to complete the point of sales process.
In addition, there are no known systems that use a mobile device and RFID tags for passive compliance and monitoring applications. For example, known systems for counting golf shots are cumbersome and require electronics on each golf club and/or switches that a user is required to operate. In addition, known devices also require active electronics, and therefore batteries in each golf club to operate. There are no known systems that allow a golfer to easily record a shot and location of a shot automatically and/or prompt a user to remember to record each shot for a particular club without a battery and active electronics on the club, for example that is not a practice shot. Known systems do not save the shots per user per course over time in a database and do not contemplate data mining the motion capture data, or shot count and distance data for example to allow for OEMs to purchase access to the database for business decision making for example.
There are no known systems that enable data mining for a large number of users related to their motion or motion of associated equipment to find patterns in the data that allows for business strategies to be determined based on heretofore undiscovered patterns related to motion. There are no known systems that enable obtain payment from OEMs, medical professionals, gaming companies or other end users to allow data mining of motion data. For at least the limitations described above there is a need for a system and method for utilizing motion capture data.
There are no known sensors that reside in a variety of formats and which may make use of a single “app” on a mobile phone for example to obtain motion data from multiple different pieces of equipment or clothing for a particular user.